A proof-of-concept study of personalized dosimetry for targeted radioligand therapy using pre-treatment diagnostic dynamic PET/CT and Monte Carlo simulation
PurposeTheranostics integrates diagnostic imaging (e.g., 18F-PSMA-1007 PET) with targeted radioligand therapy (TRT; e.g., 177Lu-PSMA-617), but personalized dosimetry remains challenging due to complex dose calculations. Current methods like Monte Carlo simulations are accurate but require impractica...
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Frontiers Media S.A.
2025-08-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2025.1600821/full |
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| author | Thanh Tai Duong Danny De Sarno Hatim Fakir Glenn Bauman Martin Martinov Rowan M. Thomson Ting-Yim Lee Ting-Yim Lee Ting-Yim Lee |
| author_facet | Thanh Tai Duong Danny De Sarno Hatim Fakir Glenn Bauman Martin Martinov Rowan M. Thomson Ting-Yim Lee Ting-Yim Lee Ting-Yim Lee |
| author_sort | Thanh Tai Duong |
| collection | DOAJ |
| description | PurposeTheranostics integrates diagnostic imaging (e.g., 18F-PSMA-1007 PET) with targeted radioligand therapy (TRT; e.g., 177Lu-PSMA-617), but personalized dosimetry remains challenging due to complex dose calculations. Current methods like Monte Carlo simulations are accurate but require impractical post-treatment multi-day SPECT/CT imaging. Here we establish a proof-of-concept framework using pre-treatment PET/CT to predict TRT doses via graphical analysis and Monte Carlo modeling, eliminating the need for serial imaging. Our voxel-based approach demonstrates significant dose variations in prostate cancer patients under standard TRT with a one-size-fits-all radioligand dose, enabling pre-treatment dose personalization—a critical step toward precision radiotheranostics.MethodsDynamic PET/CT scans obtained with 18F-DCFPyL over 22 min from six prostate cancer patients were used in this study. Tissue time-integrated activity (TIA), that is, the total number of decays from the accumulated radioligand, was calculated as the product of the area under the curve (AUC) of an extrapolated arterial time activity curve (TAC) and the Logan distribution volume (LDV) determined by graphical analysis of tissue TAC. The resulting 177Lu-PSMA-617 TIA map, along with the CT-derived tissue geometry, density, and composition maps, were used to calculate the absorbed dose in the prostate tumor, overall prostate, and bone marrow in the femurs by egs_mird, a Monte Carlo-based absorbed dose calculation. Biological effective dose (BED) was calculated using the voxel-based absorbed dose and an extended radiobiological linear quadratic model accounting for dose rate, DNA repair, and clonal repopulation.ResultsVoxel-wise LDV graphical analysis demonstrated strong linearity, with an interpatient mean R2 of 0.999973 ± 0.000047 (mean ± SD). Using a one-size-fits-all radioligand dosing approach, significant variations in absorbed dose were observed: 10.4 ± 4.9 Gy/GBq in tumors, 5.1 ± 0.7 Gy/GBq in normal prostate tissue, and 1.0 ± 0.3 Gy/GBq in bone marrow. These variations were influenced by differences in both LDV and arterial TACs among the patients—the former due to radioligand binding avidity and the latter to tumor burden and clearance rates.ConclusionWe developed a framework for personalized TRT dose calculations using pre-treatment diagnostic PET/CT scans, eliminating the need for post-treatment SPECT/CT scans via the LDV-based method. This approach addresses variability in tumor and organ-at-risk doses from one-size-fits-all radioligand dosing, enabling optimized pre-treatment planning and integration with external beam radiation therapy (EBRT) or brachytherapy, if indicated, for precise and effective therapy. This method shows promise but requires further validation through larger studies and direct comparison with post-treatment dosimetry to confirm its accuracy. |
| format | Article |
| id | doaj-art-45b90b9c98ec4e65acdc9234c913dac9 |
| institution | Kabale University |
| issn | 2234-943X |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Oncology |
| spelling | doaj-art-45b90b9c98ec4e65acdc9234c913dac92025-08-20T03:57:36ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2025-08-011510.3389/fonc.2025.16008211600821A proof-of-concept study of personalized dosimetry for targeted radioligand therapy using pre-treatment diagnostic dynamic PET/CT and Monte Carlo simulationThanh Tai Duong0Danny De Sarno1Hatim Fakir2Glenn Bauman3Martin Martinov4Rowan M. Thomson5Ting-Yim Lee6Ting-Yim Lee7Ting-Yim Lee8Robarts Research Institute, University of Western Ontario, London, ON, CanadaRobarts Research Institute, University of Western Ontario, London, ON, CanadaOncology Department, University of Western Ontario, London, ON, CanadaOncology Department, University of Western Ontario, London, ON, CanadaPhysics Department, Carleton University, Ottawa, ON, CanadaPhysics Department, Carleton University, Ottawa, ON, CanadaRobarts Research Institute, University of Western Ontario, London, ON, CanadaOncology Department, University of Western Ontario, London, ON, CanadaImaging Program, Lawson Research Institute, London, ON, CanadaPurposeTheranostics integrates diagnostic imaging (e.g., 18F-PSMA-1007 PET) with targeted radioligand therapy (TRT; e.g., 177Lu-PSMA-617), but personalized dosimetry remains challenging due to complex dose calculations. Current methods like Monte Carlo simulations are accurate but require impractical post-treatment multi-day SPECT/CT imaging. Here we establish a proof-of-concept framework using pre-treatment PET/CT to predict TRT doses via graphical analysis and Monte Carlo modeling, eliminating the need for serial imaging. Our voxel-based approach demonstrates significant dose variations in prostate cancer patients under standard TRT with a one-size-fits-all radioligand dose, enabling pre-treatment dose personalization—a critical step toward precision radiotheranostics.MethodsDynamic PET/CT scans obtained with 18F-DCFPyL over 22 min from six prostate cancer patients were used in this study. Tissue time-integrated activity (TIA), that is, the total number of decays from the accumulated radioligand, was calculated as the product of the area under the curve (AUC) of an extrapolated arterial time activity curve (TAC) and the Logan distribution volume (LDV) determined by graphical analysis of tissue TAC. The resulting 177Lu-PSMA-617 TIA map, along with the CT-derived tissue geometry, density, and composition maps, were used to calculate the absorbed dose in the prostate tumor, overall prostate, and bone marrow in the femurs by egs_mird, a Monte Carlo-based absorbed dose calculation. Biological effective dose (BED) was calculated using the voxel-based absorbed dose and an extended radiobiological linear quadratic model accounting for dose rate, DNA repair, and clonal repopulation.ResultsVoxel-wise LDV graphical analysis demonstrated strong linearity, with an interpatient mean R2 of 0.999973 ± 0.000047 (mean ± SD). Using a one-size-fits-all radioligand dosing approach, significant variations in absorbed dose were observed: 10.4 ± 4.9 Gy/GBq in tumors, 5.1 ± 0.7 Gy/GBq in normal prostate tissue, and 1.0 ± 0.3 Gy/GBq in bone marrow. These variations were influenced by differences in both LDV and arterial TACs among the patients—the former due to radioligand binding avidity and the latter to tumor burden and clearance rates.ConclusionWe developed a framework for personalized TRT dose calculations using pre-treatment diagnostic PET/CT scans, eliminating the need for post-treatment SPECT/CT scans via the LDV-based method. This approach addresses variability in tumor and organ-at-risk doses from one-size-fits-all radioligand dosing, enabling optimized pre-treatment planning and integration with external beam radiation therapy (EBRT) or brachytherapy, if indicated, for precise and effective therapy. This method shows promise but requires further validation through larger studies and direct comparison with post-treatment dosimetry to confirm its accuracy.https://www.frontiersin.org/articles/10.3389/fonc.2025.1600821/fulltargeted radioligand therapy (TRT)personalized dosimetryMonte Carlo simulationtracer kinetics177Lu-PSMA-617biological effective dose (BED) |
| spellingShingle | Thanh Tai Duong Danny De Sarno Hatim Fakir Glenn Bauman Martin Martinov Rowan M. Thomson Ting-Yim Lee Ting-Yim Lee Ting-Yim Lee A proof-of-concept study of personalized dosimetry for targeted radioligand therapy using pre-treatment diagnostic dynamic PET/CT and Monte Carlo simulation Frontiers in Oncology targeted radioligand therapy (TRT) personalized dosimetry Monte Carlo simulation tracer kinetics 177Lu-PSMA-617 biological effective dose (BED) |
| title | A proof-of-concept study of personalized dosimetry for targeted radioligand therapy using pre-treatment diagnostic dynamic PET/CT and Monte Carlo simulation |
| title_full | A proof-of-concept study of personalized dosimetry for targeted radioligand therapy using pre-treatment diagnostic dynamic PET/CT and Monte Carlo simulation |
| title_fullStr | A proof-of-concept study of personalized dosimetry for targeted radioligand therapy using pre-treatment diagnostic dynamic PET/CT and Monte Carlo simulation |
| title_full_unstemmed | A proof-of-concept study of personalized dosimetry for targeted radioligand therapy using pre-treatment diagnostic dynamic PET/CT and Monte Carlo simulation |
| title_short | A proof-of-concept study of personalized dosimetry for targeted radioligand therapy using pre-treatment diagnostic dynamic PET/CT and Monte Carlo simulation |
| title_sort | proof of concept study of personalized dosimetry for targeted radioligand therapy using pre treatment diagnostic dynamic pet ct and monte carlo simulation |
| topic | targeted radioligand therapy (TRT) personalized dosimetry Monte Carlo simulation tracer kinetics 177Lu-PSMA-617 biological effective dose (BED) |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2025.1600821/full |
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